Correlation of Water Fluoride with Body Fluids, Dental Fluorosis and FT <sub>4</sub> , FT <sub>3</sub> –TSH Disruption among Children in an Endemic Fluorosis area in Pakistan
Bibliographic record
Abstract
Abstract In the present study 134 children were studied for comparison and correlation between an endemic fluorotic village Rukh Mudke (RM), n = 74 , and a non-fluorotic village Ottawa (OTW), n = 60 . The children were aged between 7-18 years and selected for the estimation of fluoride in their household water, body fluids (urine-serum), dental fluorosis and thyroid hormones (Free tri-iodothyronine (FT 3 ) free tetra iodothyronine (FT 4 ) and thyroid stimulating hormone (TSH) respectively . Mean concentration of water fluoride in subjects of RM was 4.6 ×10 6 ng/L, urine fluoride 2.59 ×10 6 ng/L, serum fluoride 6.0 ×10 4 and dental fluorosis 90.5% respectively. Significant elevation ( P = 0.000) in the concentration of three out of these four variables ( P < 0.01) was observed (except in serum fluoride) in subjects of RM compared to those in the control group (OTW). Mean FT 4 , FT 3 and TSH concentrations in RM subjects was 18.3 pmol/L, 5.06 pmol/L and 3.2 mlU/L respectively. No marked difference in FT 4 and FT 3 ( P = 0.17 and P = 0.7) was found compared to the control (OTW) group, while significant elevation in TSH ( P < 0.05) was found in. 22% of the children in the RM group, portrayed well defined thyroid hormonal aberrations. A negative correlation between water fluoride - FT 4 (r = - 0.24); a strong positive between water, urine, serum, dental fluorosis and TSH (r = 0.94, 0.87, 0.88, 0.74 and 0.8) and moderate correlation between water fluoride - FT 3 (r = 0.52) was observed. Results of this study indicate that the fluoride intoxication through drinking water is not only increasing fluoride level in body fluids and deteriorating teeth but also destroying thyroid function in a large number of children.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".